The Application of Fuzzy Theory in Mathematics Learning: ThePrediction of Calculus Exams of TKU Students

碩士 === 淡江大學 === 數學學系碩士班 === 94 === Over the past ten years, the number of colleges in Taiwan has multiplied in the light of the boom of running schools. At present, there are over one hundred and fifty colleges, and the number of matriculated students is still increasing. In 2002, the Ministry of Ed...

Full description

Bibliographic Details
Main Authors: Dian-Yi Tsai, 蔡典益
Other Authors: 曾琇瑱
Format: Others
Language:zh-TW
Published: 2006
Online Access:http://ndltd.ncl.edu.tw/handle/75244674067082652999
Description
Summary:碩士 === 淡江大學 === 數學學系碩士班 === 94 === Over the past ten years, the number of colleges in Taiwan has multiplied in the light of the boom of running schools. At present, there are over one hundred and fifty colleges, and the number of matriculated students is still increasing. In 2002, the Ministry of Education abolished the Joint College Entrance Examination, which had been implemented for forty-eight years, and turned to thoroughly adopt a diverse entrance policy. In the past years the Ministry of Education had urged to promote the reformation of education in order to relieve students'' pressure arising from the joint entrance examination. However, due to oversimplification of some curriculums, this resulted in the deterioration of students'' learning ability. A report of China Times Express on July 28, 2005 indicated that the calculus part of the third grade senior high mathematics was deleted. This made high school students too insufficient in the preliminary special knowledge to catch up with the level of college mathematics, and calculus learning became difficult when they go to college. In this study, two sets of questionnaire are answered by the freshmen of Tamkang University, class of 2004 and 2005, to identify possible factors, which might affect students'' motivation to study calculus. Based on the identified factors, they are asked to predict the performance of their mid-term calculus examination, and the result obtained compares with the actual scores. The analysis is begun by defining the connection that appropriately conform to fuzzy preference to the two questionnaires, followed by integrating the group preference and the aggregation rule. The conventional questionnaire is then analyzed by applying a fuzzy theory. We assume that each student has different degree of fuzzy preference for the items of the questionnaire on account of their unique personal factors. Through the determination of individual fuzzy weight, total fuzzy weight, and fuzzy weight, qualitative grades (excellent, good, average, bad, and terrible) and the associated membership functions are evaluated. For those who do not express clearly about the level of their grades, the corresponding grades are predicted through the membership function-prediction of grades relation by choosing the maximum of the membership function. A comparison between the designs of the two sets of questionnaire is also made, and the results obtained discussed.